{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/entity/anaconda2/lib/python2.7/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n",
      "/home/entity/anaconda2/lib/python2.7/site-packages/sklearn/grid_search.py:43: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. This module will be removed in 0.20.\n",
      "  DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_context(\"poster\")\n",
    "sns.set_style(\"ticks\")\n",
    "\n",
    "from itertools import chain\n",
    "\n",
    "from sklearn.metrics import make_scorer\n",
    "from sklearn.cross_validation import cross_val_score\n",
    "from sklearn.grid_search import RandomizedSearchCV\n",
    "\n",
    "import sklearn_crfsuite\n",
    "from sklearn_crfsuite import scorers\n",
    "from sklearn_crfsuite import metrics\n",
    "from sklearn.cross_validation import cross_val_score\n",
    "from sklearn.grid_search import RandomizedSearchCV\n",
    "\n",
    "import regex as re\n",
    "from collections import namedtuple, defaultdict, Counter, OrderedDict\n",
    "from IPython.display import display\n",
    "from joblib import load, dump, Parallel, delayed\n",
    "\n",
    "import os, string, sys\n",
    "\n",
    "from gensim.models import word2vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class RegexFeatures(object):\n",
    "    PATTERNS = {\n",
    "        \"isInitCapitalWord\": re.compile(r'^[A-Z][a-z]+'),\n",
    "        \"isAllCapitalWord\": re.compile(r'^[A-Z][A-Z]+$'),\n",
    "        \"isAllSmallCase\": re.compile(r'^[a-z]+$'),\n",
    "        \"isWord\": re.compile(r'^[a-zA-Z][a-zA-Z]+$'),\n",
    "        \"isAlphaNumeric\": re.compile(r'^\\p{Alnum}+$'),\n",
    "        \"isSingleCapLetter\": re.compile(r'^[A-Z]$'),\n",
    "        \"containsDashes\": re.compile(r'.*--.*'),\n",
    "        \"containsDash\": re.compile(r'.*\\-.*'),\n",
    "        \"singlePunctuation\": re.compile(r'^\\p{Punct}$'),\n",
    "        \"repeatedPunctuation\": re.compile(r'^[\\.\\,!\\?\"\\':;_\\-]{2,}$'),\n",
    "        \"singleDot\": re.compile(r'[.]'),\n",
    "        \"singleComma\": re.compile(r'[,]'),\n",
    "        \"singleQuote\": re.compile(r'[\\']'),\n",
    "        \"isSpecialCharacter\": re.compile(r'^[#;:\\-/<>\\'\\\"()&]$'),\n",
    "        \"fourDigits\": re.compile(r'^\\d\\d\\d\\d$'),\n",
    "        \"isDigits\": re.compile(r'^\\d+$'),\n",
    "        \"isNumber\": re.compile(r'^((\\p{N}{,2}([,]?\\p{N}{3})+)(\\.\\p{N}+)?)$'),\n",
    "        \"containsDigit\": re.compile(r'.*\\d+.*'),\n",
    "        \"endsWithDot\": re.compile(r'\\p{Alnum}+\\.$'),\n",
    "        \"isURL\": re.compile(r'^http[s]?://'),\n",
    "        \"isMention\": re.compile(r'^(RT)?@\\p{Alnum}+$'),\n",
    "        \"isHashtag\": re.compile(r'^#\\p{Alnum}+$'),\n",
    "        \"isMoney\": re.compile(r'^\\$((\\p{N}{,2}([,]?\\p{N}{3})+)(\\.\\p{N}+)?)$'),\n",
    "    }\n",
    "    def __init__(self):\n",
    "        print \"Initialized RegexFeature\"\n",
    "    @staticmethod\n",
    "    def process(word):\n",
    "        features = dict()\n",
    "        for k, p in RegexFeatures.PATTERNS.iteritems():\n",
    "            if p.match(word):\n",
    "                features[k] = True\n",
    "        return features\n",
    "    \n",
    "    \n",
    "def classification_report_to_df(report):\n",
    "    report_list = []\n",
    "    for i, line in enumerate(report.split(\"\\n\")):\n",
    "        if i == 0:\n",
    "            report_list.append([\"class\", \"precision\", \"recall\", \"f1-score\", \"support\"])\n",
    "        else:\n",
    "            line = line.strip()\n",
    "            if line:\n",
    "                if line.startswith(\"avg\"):\n",
    "                    line = line.replace(\"avg / total\", \"avg/total\")\n",
    "                line = re.split(r'\\s+', line)\n",
    "                report_list.append(tuple(line))\n",
    "    return pd.DataFrame(report_list[1:], columns=report_list[0])\n",
    "\n",
    "\n",
    "DATA_DIR=\"data/data/\"\n",
    "CLEANED_DIR=\"data/cleaned/\"\n",
    "\n",
    "Tag = namedtuple(\"Tag\", [\"token\", \"tag\"])\n",
    "\n",
    "def load_sequences(filename, sep=\"\\t\", notypes=False, test_data=False):\n",
    "    sequences = []\n",
    "    with open(filename) as fp:\n",
    "        seq = []\n",
    "        for line in fp:\n",
    "            line = line.strip()\n",
    "            if line:\n",
    "                line = line.split(sep)\n",
    "                if test_data:\n",
    "                    assert len(line) == 1\n",
    "                    line.append(\"?\")\n",
    "                if notypes:\n",
    "                    line[1] = line[1][0]\n",
    "                seq.append(Tag(*line))\n",
    "            else:\n",
    "                sequences.append(seq)\n",
    "                seq = []\n",
    "        if seq:\n",
    "            sequences.append(seq)\n",
    "    return sequences\n",
    "\n",
    "\n",
    "def load_vocab(filename):\n",
    "    vocab = set()\n",
    "    with open(filename) as fp:\n",
    "        for line in fp:\n",
    "            line = line.strip()\n",
    "            vocab.add(line)\n",
    "    return vocab      \n",
    "\n",
    "    \n",
    "def print_transitions(trans_features):\n",
    "    for (label_from, label_to), weight in trans_features:\n",
    "        print(\"%-6s -> %-7s %0.6f\" % (label_from, label_to, weight))\n",
    "        \n",
    "def print_state_features(state_features):\n",
    "    for (attr, label), weight in state_features:\n",
    "        print(\"%0.6f %-8s %s\" % (weight, label, attr)) \n",
    "        \n",
    "        \n",
    "def plot_cm(y_test, y_pred, labels=[]):\n",
    "    labels_s = dict((k,i) for i,k in enumerate(labels))\n",
    "    cm = np.zeros((len(labels), len(labels)))\n",
    "    for i,j in zip(sum(y_test, []), sum(y_pred, [])):\n",
    "        i = labels_s[i]\n",
    "        j = labels_s[j]\n",
    "        cm[i,j] += 1\n",
    "    with plt.rc_context(rc={'xtick.labelsize': 12, 'ytick.labelsize': 12,\n",
    "                       'figure.figsize': (16,14)}):\n",
    "        sns.heatmap(cm * 100/ cm.sum(axis=1, keepdims=True),\n",
    "                    #cmap=sns.cubehelix_palette(n_colors=100, rot=-.4, as_cmap=True),\n",
    "                    cmap=\"Greys_r\",\n",
    "                    xticklabels=labels,\n",
    "                    yticklabels=labels)\n",
    "        plt.ylabel(\"True labels\")\n",
    "        plt.xlabel(\"Predicted labels\")\n",
    "    print cm.shape\n",
    "    return cm\n",
    "\n",
    "\n",
    "def print_sequences(sequences, predictions, filename, test_data=False):\n",
    "    with open(filename, \"wb+\") as fp:\n",
    "        for seq, pred in zip(sequences, predictions):\n",
    "            for t, p in zip(seq, pred):\n",
    "                token, tag = t\n",
    "                if tag[0] == \"U\":\n",
    "                    tag = \"B%s\" % tag[1:]\n",
    "                if tag[0] == \"E\":\n",
    "                    tag = \"I%s\" % tag[1:]\n",
    "                if p[0] == \"U\":\n",
    "                    p = \"B%s\" % p[1:]\n",
    "                if p[0] == \"E\":\n",
    "                    p = \"I%s\" % p[1:]\n",
    "                if test_data:\n",
    "                    line = \"\\t\".join((token, p))\n",
    "                else:\n",
    "                    line = \"\\t\".join((token, tag, p))\n",
    "                print >> fp, line\n",
    "            print >> fp, \"\"\n",
    "    print \"Done\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "WORD_SPLITTER = re.compile(r'[\\p{Punct}\\s]+')\n",
    "class DictionaryFeatures:\n",
    "    def __init__(self, dictDir):\n",
    "        self.word2dictionaries = {}\n",
    "        self.word2hashtagdictionaries = {}\n",
    "        self.dictionaries = []\n",
    "        i = 0\n",
    "        for d in os.listdir(dictDir):\n",
    "            print >> sys.stderr, \"read dict %s\"%d\n",
    "            self.dictionaries.append(d)\n",
    "            if d == '.svn':\n",
    "                continue\n",
    "            for line in open(dictDir + \"/\" + d):\n",
    "                word = line.rstrip('\\n')\n",
    "                word = word.strip(' ').lower()\n",
    "                word_hashtag = \"\".join(WORD_SPLITTER.split(word))\n",
    "                if not self.word2dictionaries.has_key(word):\n",
    "                    self.word2dictionaries[word] = str(i)\n",
    "                else:   \n",
    "                    self.word2dictionaries[word] += \"\\t%s\" % i\n",
    "                if not self.word2hashtagdictionaries.has_key(word_hashtag):\n",
    "                    self.word2hashtagdictionaries[word_hashtag] = str(i)\n",
    "                else:\n",
    "                    self.word2hashtagdictionaries[word_hashtag] += \"\\t%s\" % i\n",
    "            i += 1\n",
    "    \n",
    "    MAX_WINDOW_SIZE=6\n",
    "    def GetDictFeatures(self, words, i):\n",
    "        features = []\n",
    "        for window in range(1,self.MAX_WINDOW_SIZE):\n",
    "            start=max(i-window+1, 0)\n",
    "            end = start + window\n",
    "            phrase = ' '.join(words[start:end]).lower().strip(string.punctuation)\n",
    "            if self.word2dictionaries.has_key(phrase):\n",
    "                for j in self.word2dictionaries[phrase].split('\\t'):\n",
    "                    features.append('DICT=%s' % self.dictionaries[int(j)])\n",
    "                if window > 1:\n",
    "                    features.append('DICTWIN=%s' % window)\n",
    "        return list(set(features))\n",
    "    \n",
    "    def GetHashtagDictFeatures(self, word):\n",
    "        features = []\n",
    "        if len(word) < 2 or word[0] != \"#\":\n",
    "            return features\n",
    "        word = word[1:].lower().strip(string.punctuation)\n",
    "        if self.word2hashtagdictionaries.has_key(word):\n",
    "            for j in self.word2hashtagdictionaries[word].split('\\t'):\n",
    "                features.append('DICT_HASHTAG=%s' % self.dictionaries[int(j)])\n",
    "        return list(set(features))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8023\n"
     ]
    }
   ],
   "source": [
    "train_sequences = load_sequences(\"data/cleaned/train.BIEOU.tsv\", sep=\"\\t\", notypes=False)\n",
    "dev_sequences = (load_sequences(\"data/cleaned/dev.BIEOU.tsv\", sep=\"\\t\", notypes=False) \n",
    "                 + load_sequences(\"data/cleaned/dev_2015.BIEOU.tsv\", sep=\"\\t\", notypes=False))\n",
    "test_sequences = load_sequences(\"data/cleaned/test.BIEOU.tsv\", sep=\"\\t\", notypes=False)\n",
    "vocab = load_vocab(\"vocab.no_extras.txt\")\n",
    "print len(vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'product': 5, 'facility': 4, 'movie': 8, 'company': 3, 'sportsteam': 7, 'musicartist': 6, 'person': 1, 'other': 2, 'geo-loc': 0, 'tvshow': 9}\n",
      "Counter({'geo-loc': 1323, 'person': 1180, 'other': 995, 'company': 865, 'facility': 404, 'product': 390, 'musicartist': 304, 'sportsteam': 303, 'movie': 86, 'tvshow': 75})\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAskAAAJBCAYAAAC01ihYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5afe735c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "label_co_occurences = [[t[1][2:] for t in seq if t[1][0] in [\"B\", \"U\"]] \n",
    "                       for seq in (train_sequences+dev_sequences+test_sequences)]\n",
    "\n",
    "cat_types = Counter(t for seq in label_co_occurences for t in seq)\n",
    "cat_ids = {k[0]: i for i, k in enumerate(cat_types.most_common())}\n",
    "cat_names = [k[0] for k in cat_types.most_common()]\n",
    "print cat_ids\n",
    "print cat_types\n",
    "co_occur_matrix = np.zeros((len(cat_ids), len(cat_ids)))\n",
    "for seq in label_co_occurences:\n",
    "    for i, t in enumerate(seq):\n",
    "        for j, t1 in enumerate(seq):\n",
    "            if i != j:\n",
    "                co_occur_matrix[cat_ids[t], cat_ids[t1]] += 1\n",
    "for k,i in cat_ids.iteritems():\n",
    "    co_occur_matrix[cat_ids[k]] /= co_occur_matrix[cat_ids[k]].sum()\n",
    "    \n",
    "#print co_occur_matrix\n",
    "    \n",
    "with plt.rc_context(rc={'xtick.labelsize': 10, 'ytick.labelsize': 10,\n",
    "                        'font.size': 8,\n",
    "                       'figure.figsize': (8,6)}):\n",
    "    sns.heatmap(co_occur_matrix, xticklabels=cat_names, yticklabels=cat_names, annot=True, cmap=\"Greys\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Num entities in Training data (N=2394, N_entities=1499, N(no-entities)=1476): min=0, max=6, median=0.0, mean(+/-std)=0.6 +/- 1.0\n",
      "Num entities in Development data (N=1420, N_entities=937, N(no-entities)=838): min=0, max=9, median=0.0, mean(+/-std)=0.7 +/- 1.0\n",
      "Num entities in Test data (N=3856, N_entities=3489, N(no-entities)=1842): min=0, max=11, median=1.0, mean(+/-std)=0.9 +/- 1.1\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5afe735790>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABFoAAAMSCAYAAABakqAcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b047c6a50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_lens = []\n",
    "for sequences, label in zip((train_sequences, dev_sequences, test_sequences),\n",
    "                       (\"Training\", \"Development\", \"Test\")):\n",
    "    lens = [len([t[1][2:] for t in seq if t[1][0] in [\"B\", \"U\"]])\n",
    "                       for seq in (sequences)]\n",
    "    total_lens.extend([(t, label) for t in lens])\n",
    "    print \"Num entities in {} data (N={}, N_entities={}, N(no-entities)={}): min={}, max={}, median={}, mean(+/-std)={:.1f} +/- {:.1f}\".format(\n",
    "        label, len(lens), sum(lens), len(filter(lambda x: x==0, lens)),\n",
    "        min(lens), max(lens), np.median(lens), np.mean(lens), np.std(lens))\n",
    "sns.countplot(x=\"num_entities\", hue=\"data\", data=pd.DataFrame(total_lens, columns=[\"num_entities\", \"data\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1842"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(filter(lambda x: x==0, lens))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.7.1'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sns.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entity length in Training data (N=1499, N_entities=2462): min=1, max=10, median=1.0, mean(+/-std)=1.6 +/- 1.0\n",
      "Entity length in Development data (N=937, N_entities=1567): min=1, max=14, median=1.0, mean(+/-std)=1.7 +/- 1.2\n",
      "Entity length in Test data (N=3489, N_entities=5955): min=1, max=14, median=1.0, mean(+/-std)=1.7 +/- 1.2\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABTcAAAuPCAYAAAAtErvmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5afe4af090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_lens = []\n",
    "for sequences, label in zip((train_sequences, dev_sequences, test_sequences),\n",
    "                       (\"Training\", \"Development\", \"Test\")):\n",
    "    lens = []\n",
    "    for seq in sequences:\n",
    "        e_length=0\n",
    "        e_type=None\n",
    "        for t in seq:\n",
    "            if t[1][0] == \"O\":\n",
    "                continue\n",
    "            if t[1][0] in {\"B\", \"U\"}:\n",
    "                if e_length > 0:\n",
    "                    lens.append((e_length, e_type))\n",
    "                e_length=0\n",
    "                e_type=t[1][2:]\n",
    "            e_length += 1\n",
    "        if e_length > 0:\n",
    "            lens.append((e_length, e_type))\n",
    "    total_lens.extend([t+(label,) for t in lens])\n",
    "    lens = [t[0] for t in lens]\n",
    "    print \"Entity length in {} data (N={}, N_entities={}): min={}, max={}, median={}, mean(+/-std)={:.1f} +/- {:.1f}\".format(\n",
    "        label, len(lens), sum(lens), min(lens), max(lens), np.median(lens), np.mean(lens), np.std(lens))\n",
    "\n",
    "def plot_data(x, **kwargs):\n",
    "    weights = np.ones_like(x)*1./len(x)\n",
    "    return plt.hist(x, weights=weights, **kwargs)\n",
    "g = (sns.FacetGrid(row=\"entity_type\", col=\"data\", aspect=1.5, margin_titles=True,\n",
    "                  data=pd.DataFrame(total_lens, columns=[\"entity_lengths\", \"entity_type\", \"data\"])))\n",
    "g = g.map(plot_data, \"entity_lengths\", bins=range(1,10))\n",
    "g = g.set_titles(template=\"\", col_template=\"{col_name}\")\n",
    "g.fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['person', 'geo-loc', 'other', 'company', 'facility', 'product', 'musicartist', 'sportsteam', 'movie', 'tvshow']\n",
      "Training sequences: 2394\n",
      "Development sequences: 1420\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2kAAAHlCAYAAABvZbQsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQgghhDAgEqQJIYQQQgghhAH5H9SVA9cyJ0gGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5af6c4a5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "phrase_types_training = [(t[1][2:], \"training\") for seq in (train_sequences) for t in seq if t[1][0] in [\"B\", \"U\"]]\n",
    "phrase_types_dev = [(t[1][2:], \"dev\") for seq in (dev_sequences) for t in seq if t[1][0] in [\"B\", \"U\"]]\n",
    "phrase_types_test = [(t[1][2:], \"test\") for seq in (test_sequences) for t in seq if t[1][0] in [\"B\", \"U\"]]\n",
    "df_t = pd.DataFrame(phrase_types_training+phrase_types_dev+phrase_types_test, columns=[\"phrase_type\", \"data\"])\n",
    "cat_names = [k[0] for k,v in Counter(phrase_types_training).most_common()]\n",
    "print cat_names\n",
    "#palette = [\"0.2\", \"0.5\", \"0.7\"]\n",
    "palette = [\"black\", \"yellow\", \"red\"]\n",
    "with plt.rc_context(rc={'xtick.labelsize': 10, 'ytick.labelsize': 10,\n",
    "                        'font.size': 10,\n",
    "                       'figure.figsize': (10,5)}):\n",
    "    ax = sns.countplot(x=\"phrase_type\", hue=\"data\", data=df_t,\n",
    "                       palette=palette, order=cat_names)\n",
    "    ax.set_xticklabels(ax.get_xticklabels(), rotation='vertical')\n",
    "    plt.xlabel(\"Entity Types\")\n",
    "    plt.ylabel(\"Frequency\")\n",
    "    plt.margins(0.01)\n",
    "    sns.despine(offset=2)\n",
    "    for p in ax.patches:\n",
    "        height = p.get_height()\n",
    "        ax.text(p.get_x(), height+3, '%.0f'%(height))\n",
    "        \n",
    "print \"Training sequences: {}\".format(len(train_sequences))\n",
    "print \"Development sequences: {}\".format(len(dev_sequences))\n",
    "df_t.data.value_counts()\n",
    "plt.savefig(\"Data.tiff\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[6, 1, 2, 1, 1, 1, 2, 3, 1, 9]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lens[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('other', 'test'),\n",
       " ('movie', 'test'),\n",
       " ('person', 'test'),\n",
       " ('person', 'test'),\n",
       " ('geo-loc', 'test'),\n",
       " ('person', 'test'),\n",
       " ('company', 'test'),\n",
       " ('company', 'test'),\n",
       " ('geo-loc', 'test'),\n",
       " ('product', 'test')]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phrase_types_test[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training lengths: 19.4 +/- 7.6\n",
      "Development lengths: 16.2 +/- 6.8\n",
      "Test lengths: 16.1 +/- 6.6\n"
     ]
    }
   ],
   "source": [
    "train_lens = [len(seq) for seq in train_sequences]\n",
    "dev_lens = [len(seq) for seq in dev_sequences]\n",
    "test_lens = [len(seq) for seq in test_sequences]\n",
    "for lens, label in zip((train_lens, dev_lens, test_lens),\n",
    "                       (\"Training\", \"Development\", \"Test\")):\n",
    "    print \"{0} lengths: {1:.1f} +/- {2:.1f}\".format(\n",
    "        label, np.mean(lens), np.std(lens))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training phrase counts: 0 - 6\n",
      "Development phrase counts: 0 - 9\n",
      "Test phrase counts: 0 - 11\n"
     ]
    }
   ],
   "source": [
    "for sequences, label in zip((train_sequences, dev_sequences, test_sequences),\n",
    "                       (\"Training\", \"Development\", \"Test\")):\n",
    "    phrase_counts = [len([t[1][2:] for t in seq if t[1][0] in [\"B\", \"U\"]])\n",
    "                       for seq in (sequences)]\n",
    "    print \"{} phrase counts: {} - {}\".format(label,\n",
    "        np.min(phrase_counts), np.max(phrase_counts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = \"\"\"F\tMF\t+GZ\t+WRG\t+WCBPT\t+WCCC\t+WRFTC\t+GF\t+RSFD\tST\tBL\n",
    "10-types\t5.32\t34.8\t36.66\t41.59\t41.04\t43.3\t40.94\t\t36.22\t35.1\n",
    "company\t0\t30\t34.53\t33.33\t35.2\t33.33\t32\t\t27.72\t26.17\n",
    "facility\t0\t12.35\t9.62\t20.78\t18.56\t17.91\t14.49\t\t30.38\t19.15\n",
    "geo-loc\t5.24\t47.21\t48.06\t53.83\t54.4\t55.93\t56.73\t\t49.71\t48.36\n",
    "movie\t8\t7.41\t6.45\t8.33\t7.69\t9.52\t23.53\t\t8.33\t0\n",
    "musicartist\t0\t6.56\t8.45\t9.09\t9.52\t12.7\t6.45\t\t0\t0\n",
    "other\t5.79\t18.56\t18.69\t22.54\t20.85\t26.63\t22.11\t\t24.16\t27.74\n",
    "person\t11.37\t55.07\t58.51\t63.39\t63.81\t64.82\t64.96\t\t53.36\t50.18\n",
    "product\t2.92\t12.66\t20\t16.67\t18.18\t15.38\t10.75\t\t8.96\t11.9\n",
    "sportsteam\t0\t12.9\t27.94\t30.53\t29.01\t28.13\t27.69\t\t12.8\t13.11\n",
    "tvshow\t0\t0\t0\t16.67\t16.67\t16.67\t18.18\t\t0\t14.29\n",
    "No-types\t13.13\t48.31\t52.51\t56.73\t56.41\t57.38\t53.67\t\t50.53\t51.71\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=11, step=1)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_t = pd.DataFrame([[t.strip() for t in line.split(\"\\t\")] for line in data.split(\"\\n\")[1:]])\n",
    "#df_t.columns = data.split(\"\\n\")[0].split()\n",
    "df_t.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data.split(\"\\n\")[0].split(\"\\t\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(12, 11)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_t.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>F</th>\n",
       "      <th>MF</th>\n",
       "      <th>+GZ</th>\n",
       "      <th>+WRG</th>\n",
       "      <th>+WCBPT</th>\n",
       "      <th>+WCCC</th>\n",
       "      <th>+WRFTC</th>\n",
       "      <th>+GF</th>\n",
       "      <th>+RSFD</th>\n",
       "      <th>ST</th>\n",
       "      <th>BL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10-types</td>\n",
       "      <td>5.32</td>\n",
       "      <td>34.8</td>\n",
       "      <td>36.66</td>\n",
       "      <td>41.59</td>\n",
       "      <td>41.04</td>\n",
       "      <td>43.3</td>\n",
       "      <td>40.94</td>\n",
       "      <td></td>\n",
       "      <td>36.22</td>\n",
       "      <td>35.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>company</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>34.53</td>\n",
       "      <td>33.33</td>\n",
       "      <td>35.2</td>\n",
       "      <td>33.33</td>\n",
       "      <td>32</td>\n",
       "      <td></td>\n",
       "      <td>27.72</td>\n",
       "      <td>26.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>facility</td>\n",
       "      <td>0</td>\n",
       "      <td>12.35</td>\n",
       "      <td>9.62</td>\n",
       "      <td>20.78</td>\n",
       "      <td>18.56</td>\n",
       "      <td>17.91</td>\n",
       "      <td>14.49</td>\n",
       "      <td></td>\n",
       "      <td>30.38</td>\n",
       "      <td>19.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>geo-loc</td>\n",
       "      <td>5.24</td>\n",
       "      <td>47.21</td>\n",
       "      <td>48.06</td>\n",
       "      <td>53.83</td>\n",
       "      <td>54.4</td>\n",
       "      <td>55.93</td>\n",
       "      <td>56.73</td>\n",
       "      <td></td>\n",
       "      <td>49.71</td>\n",
       "      <td>48.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>movie</td>\n",
       "      <td>8</td>\n",
       "      <td>7.41</td>\n",
       "      <td>6.45</td>\n",
       "      <td>8.33</td>\n",
       "      <td>7.69</td>\n",
       "      <td>9.52</td>\n",
       "      <td>23.53</td>\n",
       "      <td></td>\n",
       "      <td>8.33</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>musicartist</td>\n",
       "      <td>0</td>\n",
       "      <td>6.56</td>\n",
       "      <td>8.45</td>\n",
       "      <td>9.09</td>\n",
       "      <td>9.52</td>\n",
       "      <td>12.7</td>\n",
       "      <td>6.45</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>other</td>\n",
       "      <td>5.79</td>\n",
       "      <td>18.56</td>\n",
       "      <td>18.69</td>\n",
       "      <td>22.54</td>\n",
       "      <td>20.85</td>\n",
       "      <td>26.63</td>\n",
       "      <td>22.11</td>\n",
       "      <td></td>\n",
       "      <td>24.16</td>\n",
       "      <td>27.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>person</td>\n",
       "      <td>11.37</td>\n",
       "      <td>55.07</td>\n",
       "      <td>58.51</td>\n",
       "      <td>63.39</td>\n",
       "      <td>63.81</td>\n",
       "      <td>64.82</td>\n",
       "      <td>64.96</td>\n",
       "      <td></td>\n",
       "      <td>53.36</td>\n",
       "      <td>50.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>product</td>\n",
       "      <td>2.92</td>\n",
       "      <td>12.66</td>\n",
       "      <td>20</td>\n",
       "      <td>16.67</td>\n",
       "      <td>18.18</td>\n",
       "      <td>15.38</td>\n",
       "      <td>10.75</td>\n",
       "      <td></td>\n",
       "      <td>8.96</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>sportsteam</td>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>27.94</td>\n",
       "      <td>30.53</td>\n",
       "      <td>29.01</td>\n",
       "      <td>28.13</td>\n",
       "      <td>27.69</td>\n",
       "      <td></td>\n",
       "      <td>12.8</td>\n",
       "      <td>13.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>tvshow</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16.67</td>\n",
       "      <td>16.67</td>\n",
       "      <td>16.67</td>\n",
       "      <td>18.18</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>14.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>No-types</td>\n",
       "      <td>13.13</td>\n",
       "      <td>48.31</td>\n",
       "      <td>52.51</td>\n",
       "      <td>56.73</td>\n",
       "      <td>56.41</td>\n",
       "      <td>57.38</td>\n",
       "      <td>53.67</td>\n",
       "      <td></td>\n",
       "      <td>50.53</td>\n",
       "      <td>51.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              F     MF    +GZ   +WRG +WCBPT  +WCCC +WRFTC    +GF +RSFD     ST  \\\n",
       "0      10-types   5.32   34.8  36.66  41.59  41.04   43.3  40.94        36.22   \n",
       "1       company      0     30  34.53  33.33   35.2  33.33     32        27.72   \n",
       "2      facility      0  12.35   9.62  20.78  18.56  17.91  14.49        30.38   \n",
       "3       geo-loc   5.24  47.21  48.06  53.83   54.4  55.93  56.73        49.71   \n",
       "4         movie      8   7.41   6.45   8.33   7.69   9.52  23.53         8.33   \n",
       "5   musicartist      0   6.56   8.45   9.09   9.52   12.7   6.45            0   \n",
       "6         other   5.79  18.56  18.69  22.54  20.85  26.63  22.11        24.16   \n",
       "7        person  11.37  55.07  58.51  63.39  63.81  64.82  64.96        53.36   \n",
       "8       product   2.92  12.66     20  16.67  18.18  15.38  10.75         8.96   \n",
       "9    sportsteam      0   12.9  27.94  30.53  29.01  28.13  27.69         12.8   \n",
       "10       tvshow      0      0      0  16.67  16.67  16.67  18.18            0   \n",
       "11     No-types  13.13  48.31  52.51  56.73  56.41  57.38  53.67        50.53   \n",
       "\n",
       "       BL  \n",
       "0    35.1  \n",
       "1   26.17  \n",
       "2   19.15  \n",
       "3   48.36  \n",
       "4       0  \n",
       "5       0  \n",
       "6   27.74  \n",
       "7   50.18  \n",
       "8    11.9  \n",
       "9   13.11  \n",
       "10  14.29  \n",
       "11  51.71  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_t.columns = data.split(\"\\n\")[0].split(\"\\t\")\n",
    "df_t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>F</th>\n",
       "      <th>MF</th>\n",
       "      <th>+GZ</th>\n",
       "      <th>+WRG</th>\n",
       "      <th>+WCBPT</th>\n",
       "      <th>+WCCC</th>\n",
       "      <th>+WRFTC</th>\n",
       "      <th>+GF</th>\n",
       "      <th>+RSFD</th>\n",
       "      <th>ST</th>\n",
       "      <th>BL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10-types</td>\n",
       "      <td>5.32</td>\n",
       "      <td>34.8</td>\n",
       "      <td>36.66</td>\n",
       "      <td>41.59</td>\n",
       "      <td>41.04</td>\n",
       "      <td>43.3</td>\n",
       "      <td>40.94</td>\n",
       "      <td></td>\n",
       "      <td>36.22</td>\n",
       "      <td>35.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          F    MF   +GZ   +WRG +WCBPT  +WCCC +WRFTC    +GF +RSFD     ST    BL\n",
       "0  10-types  5.32  34.8  36.66  41.59  41.04   43.3  40.94        36.22  35.1"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_t[df_t[\"F\"] == \"10-types\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MF</th>\n",
       "      <th>+GZ</th>\n",
       "      <th>+WRG</th>\n",
       "      <th>+WCBPT</th>\n",
       "      <th>+WCCC</th>\n",
       "      <th>+WRFTC</th>\n",
       "      <th>+GF</th>\n",
       "      <th>+RSFD</th>\n",
       "      <th>ST</th>\n",
       "      <th>BL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10-types</th>\n",
       "      <td>5.32</td>\n",
       "      <td>34.8</td>\n",
       "      <td>36.66</td>\n",
       "      <td>41.59</td>\n",
       "      <td>41.04</td>\n",
       "      <td>43.3</td>\n",
       "      <td>40.94</td>\n",
       "      <td></td>\n",
       "      <td>36.22</td>\n",
       "      <td>35.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>company</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>34.53</td>\n",
       "      <td>33.33</td>\n",
       "      <td>35.2</td>\n",
       "      <td>33.33</td>\n",
       "      <td>32</td>\n",
       "      <td></td>\n",
       "      <td>27.72</td>\n",
       "      <td>26.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>facility</th>\n",
       "      <td>0</td>\n",
       "      <td>12.35</td>\n",
       "      <td>9.62</td>\n",
       "      <td>20.78</td>\n",
       "      <td>18.56</td>\n",
       "      <td>17.91</td>\n",
       "      <td>14.49</td>\n",
       "      <td></td>\n",
       "      <td>30.38</td>\n",
       "      <td>19.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>geo-loc</th>\n",
       "      <td>5.24</td>\n",
       "      <td>47.21</td>\n",
       "      <td>48.06</td>\n",
       "      <td>53.83</td>\n",
       "      <td>54.4</td>\n",
       "      <td>55.93</td>\n",
       "      <td>56.73</td>\n",
       "      <td></td>\n",
       "      <td>49.71</td>\n",
       "      <td>48.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>movie</th>\n",
       "      <td>8</td>\n",
       "      <td>7.41</td>\n",
       "      <td>6.45</td>\n",
       "      <td>8.33</td>\n",
       "      <td>7.69</td>\n",
       "      <td>9.52</td>\n",
       "      <td>23.53</td>\n",
       "      <td></td>\n",
       "      <td>8.33</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>musicartist</th>\n",
       "      <td>0</td>\n",
       "      <td>6.56</td>\n",
       "      <td>8.45</td>\n",
       "      <td>9.09</td>\n",
       "      <td>9.52</td>\n",
       "      <td>12.7</td>\n",
       "      <td>6.45</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other</th>\n",
       "      <td>5.79</td>\n",
       "      <td>18.56</td>\n",
       "      <td>18.69</td>\n",
       "      <td>22.54</td>\n",
       "      <td>20.85</td>\n",
       "      <td>26.63</td>\n",
       "      <td>22.11</td>\n",
       "      <td></td>\n",
       "      <td>24.16</td>\n",
       "      <td>27.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>person</th>\n",
       "      <td>11.37</td>\n",
       "      <td>55.07</td>\n",
       "      <td>58.51</td>\n",
       "      <td>63.39</td>\n",
       "      <td>63.81</td>\n",
       "      <td>64.82</td>\n",
       "      <td>64.96</td>\n",
       "      <td></td>\n",
       "      <td>53.36</td>\n",
       "      <td>50.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product</th>\n",
       "      <td>2.92</td>\n",
       "      <td>12.66</td>\n",
       "      <td>20</td>\n",
       "      <td>16.67</td>\n",
       "      <td>18.18</td>\n",
       "      <td>15.38</td>\n",
       "      <td>10.75</td>\n",
       "      <td></td>\n",
       "      <td>8.96</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sportsteam</th>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>27.94</td>\n",
       "      <td>30.53</td>\n",
       "      <td>29.01</td>\n",
       "      <td>28.13</td>\n",
       "      <td>27.69</td>\n",
       "      <td></td>\n",
       "      <td>12.8</td>\n",
       "      <td>13.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tvshow</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16.67</td>\n",
       "      <td>16.67</td>\n",
       "      <td>16.67</td>\n",
       "      <td>18.18</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>14.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No-types</th>\n",
       "      <td>13.13</td>\n",
       "      <td>48.31</td>\n",
       "      <td>52.51</td>\n",
       "      <td>56.73</td>\n",
       "      <td>56.41</td>\n",
       "      <td>57.38</td>\n",
       "      <td>53.67</td>\n",
       "      <td></td>\n",
       "      <td>50.53</td>\n",
       "      <td>51.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                MF    +GZ   +WRG +WCBPT  +WCCC +WRFTC    +GF +RSFD     ST  \\\n",
       "F                                                                           \n",
       "10-types      5.32   34.8  36.66  41.59  41.04   43.3  40.94        36.22   \n",
       "company          0     30  34.53  33.33   35.2  33.33     32        27.72   \n",
       "facility         0  12.35   9.62  20.78  18.56  17.91  14.49        30.38   \n",
       "geo-loc       5.24  47.21  48.06  53.83   54.4  55.93  56.73        49.71   \n",
       "movie            8   7.41   6.45   8.33   7.69   9.52  23.53         8.33   \n",
       "musicartist      0   6.56   8.45   9.09   9.52   12.7   6.45            0   \n",
       "other         5.79  18.56  18.69  22.54  20.85  26.63  22.11        24.16   \n",
       "person       11.37  55.07  58.51  63.39  63.81  64.82  64.96        53.36   \n",
       "product       2.92  12.66     20  16.67  18.18  15.38  10.75         8.96   \n",
       "sportsteam       0   12.9  27.94  30.53  29.01  28.13  27.69         12.8   \n",
       "tvshow           0      0      0  16.67  16.67  16.67  18.18            0   \n",
       "No-types     13.13  48.31  52.51  56.73  56.41  57.38  53.67        50.53   \n",
       "\n",
       "                BL  \n",
       "F                   \n",
       "10-types      35.1  \n",
       "company      26.17  \n",
       "facility     19.15  \n",
       "geo-loc      48.36  \n",
       "movie            0  \n",
       "musicartist      0  \n",
       "other        27.74  \n",
       "person       50.18  \n",
       "product       11.9  \n",
       "sportsteam   13.11  \n",
       "tvshow       14.29  \n",
       "No-types     51.71  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_t=df_t.set_index(\"F\")\n",
    "df_t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MF</th>\n",
       "      <th>+GZ</th>\n",
       "      <th>+WRG</th>\n",
       "      <th>+WCBPT</th>\n",
       "      <th>+WCCC</th>\n",
       "      <th>+WRFTC</th>\n",
       "      <th>+GF</th>\n",
       "      <th>ST</th>\n",
       "      <th>BL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10-types</th>\n",
       "      <td>5.32</td>\n",
       "      <td>34.8</td>\n",
       "      <td>36.66</td>\n",
       "      <td>41.59</td>\n",
       "      <td>41.04</td>\n",
       "      <td>43.3</td>\n",
       "      <td>40.94</td>\n",
       "      <td>36.22</td>\n",
       "      <td>35.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>company</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>34.53</td>\n",
       "      <td>33.33</td>\n",
       "      <td>35.2</td>\n",
       "      <td>33.33</td>\n",
       "      <td>32</td>\n",
       "      <td>27.72</td>\n",
       "      <td>26.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>facility</th>\n",
       "      <td>0</td>\n",
       "      <td>12.35</td>\n",
       "      <td>9.62</td>\n",
       "      <td>20.78</td>\n",
       "      <td>18.56</td>\n",
       "      <td>17.91</td>\n",
       "      <td>14.49</td>\n",
       "      <td>30.38</td>\n",
       "      <td>19.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>geo-loc</th>\n",
       "      <td>5.24</td>\n",
       "      <td>47.21</td>\n",
       "      <td>48.06</td>\n",
       "      <td>53.83</td>\n",
       "      <td>54.4</td>\n",
       "      <td>55.93</td>\n",
       "      <td>56.73</td>\n",
       "      <td>49.71</td>\n",
       "      <td>48.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>movie</th>\n",
       "      <td>8</td>\n",
       "      <td>7.41</td>\n",
       "      <td>6.45</td>\n",
       "      <td>8.33</td>\n",
       "      <td>7.69</td>\n",
       "      <td>9.52</td>\n",
       "      <td>23.53</td>\n",
       "      <td>8.33</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>musicartist</th>\n",
       "      <td>0</td>\n",
       "      <td>6.56</td>\n",
       "      <td>8.45</td>\n",
       "      <td>9.09</td>\n",
       "      <td>9.52</td>\n",
       "      <td>12.7</td>\n",
       "      <td>6.45</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other</th>\n",
       "      <td>5.79</td>\n",
       "      <td>18.56</td>\n",
       "      <td>18.69</td>\n",
       "      <td>22.54</td>\n",
       "      <td>20.85</td>\n",
       "      <td>26.63</td>\n",
       "      <td>22.11</td>\n",
       "      <td>24.16</td>\n",
       "      <td>27.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>person</th>\n",
       "      <td>11.37</td>\n",
       "      <td>55.07</td>\n",
       "      <td>58.51</td>\n",
       "      <td>63.39</td>\n",
       "      <td>63.81</td>\n",
       "      <td>64.82</td>\n",
       "      <td>64.96</td>\n",
       "      <td>53.36</td>\n",
       "      <td>50.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product</th>\n",
       "      <td>2.92</td>\n",
       "      <td>12.66</td>\n",
       "      <td>20</td>\n",
       "      <td>16.67</td>\n",
       "      <td>18.18</td>\n",
       "      <td>15.38</td>\n",
       "      <td>10.75</td>\n",
       "      <td>8.96</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sportsteam</th>\n",
       "      <td>0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>27.94</td>\n",
       "      <td>30.53</td>\n",
       "      <td>29.01</td>\n",
       "      <td>28.13</td>\n",
       "      <td>27.69</td>\n",
       "      <td>12.8</td>\n",
       "      <td>13.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tvshow</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16.67</td>\n",
       "      <td>16.67</td>\n",
       "      <td>16.67</td>\n",
       "      <td>18.18</td>\n",
       "      <td>0</td>\n",
       "      <td>14.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No-types</th>\n",
       "      <td>13.13</td>\n",
       "      <td>48.31</td>\n",
       "      <td>52.51</td>\n",
       "      <td>56.73</td>\n",
       "      <td>56.41</td>\n",
       "      <td>57.38</td>\n",
       "      <td>53.67</td>\n",
       "      <td>50.53</td>\n",
       "      <td>51.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                MF    +GZ   +WRG +WCBPT  +WCCC +WRFTC    +GF     ST     BL\n",
       "F                                                                         \n",
       "10-types      5.32   34.8  36.66  41.59  41.04   43.3  40.94  36.22   35.1\n",
       "company          0     30  34.53  33.33   35.2  33.33     32  27.72  26.17\n",
       "facility         0  12.35   9.62  20.78  18.56  17.91  14.49  30.38  19.15\n",
       "geo-loc       5.24  47.21  48.06  53.83   54.4  55.93  56.73  49.71  48.36\n",
       "movie            8   7.41   6.45   8.33   7.69   9.52  23.53   8.33      0\n",
       "musicartist      0   6.56   8.45   9.09   9.52   12.7   6.45      0      0\n",
       "other         5.79  18.56  18.69  22.54  20.85  26.63  22.11  24.16  27.74\n",
       "person       11.37  55.07  58.51  63.39  63.81  64.82  64.96  53.36  50.18\n",
       "product       2.92  12.66     20  16.67  18.18  15.38  10.75   8.96   11.9\n",
       "sportsteam       0   12.9  27.94  30.53  29.01  28.13  27.69   12.8  13.11\n",
       "tvshow           0      0      0  16.67  16.67  16.67  18.18      0  14.29\n",
       "No-types     13.13  48.31  52.51  56.73  56.41  57.38  53.67  50.53  51.71"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_t = df_t.drop(\"+RSFD\", axis=1)\n",
    "df_t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_t = df_t.astype(\"float\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>10-types</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MF</th>\n",
       "      <td>5.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>+GZ</th>\n",
       "      <td>34.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>+WRG</th>\n",
       "      <td>36.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>+WCBPT</th>\n",
       "      <td>41.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>+WCCC</th>\n",
       "      <td>41.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>+WRFTC</th>\n",
       "      <td>43.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>+GF</th>\n",
       "      <td>40.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ST</th>\n",
       "      <td>36.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BL</th>\n",
       "      <td>35.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        10-types\n",
       "MF          5.32\n",
       "+GZ        34.80\n",
       "+WRG       36.66\n",
       "+WCBPT     41.59\n",
       "+WCCC      41.04\n",
       "+WRFTC     43.30\n",
       "+GF        40.94\n",
       "ST         36.22\n",
       "BL         35.10"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(df_t.ix[\"10-types\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_tt = pd.DataFrame(df_t.ix[\"10-types\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5af7577e50>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABEQAAAL4CAYAAAByXSIXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nzv8DgbhXhKjRzasAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5afe735710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.barplot(y=\"10-types\", x=df_tt.index, data=df_tt, color=\"red\")\n",
    "sns.despine(offset=2)\n",
    "for p in ax.patches:\n",
    "        height = p.get_height()\n",
    "        ax.text(p.get_x(), height+1, '%.2f'%(height))\n",
    "        \n",
    "ax.patches[-2].set_color(\"0.4\")\n",
    "p.set_color(\"0.2\")\n",
    "ax.set_ylabel(\"Overall FB=1 score on 10-types\")\n",
    "\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
